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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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VII. Our Earthuman Ascent: A Major Evolutionary Transition in Individuality

3. Planetary Physiosphere: Anatomics, Economics, Urbanomics

Bar Yam, Yaneer. Complexity Rising: From Human Beings to Human Civilization. www.necsi.org/Civilization. Systems scientist Bar Yam provides a unique application of complexity and network theories to the structural course of human history. By these insights, human persons can now be perceived in the midst of an epic transformation into a potentially salutary, globally interconnected, superorganic society.

Our complex social environment is consistent with identifying global human civilization as an organism capable of complex behavior that protects its components (us) and which should be capable of responding effectively to complex environmental demands. (1) What is generally not recognized is that the relationship between collective global behavior and the internal structure of human civilization can be characterized through mathematical concepts that apply to all complex systems. (1)

Bar Yam, Yaneer. Dynamics of Complex Systems. Reading, MA: Addison-Wesley, 1997. After 800 pages of an accessible theoretical basis, the course of history is seen to be guided by constant self-organizing dynamics as it spirals and emerges from an individual level to a superorganic phase. At its origin a human person was more complex than society. But human population has now so increased and migrated that composite humankind has become more complex than its constituents. But within this global unity a creative reciprocity is again seen to enhance personal liberty and welfare.

In the context of considering human civilization as an organism in relation to individuals, we should revisit the traditional conflict between individual and collective good and rights. This philosophical and practical conflict manifested itself in the conflict between democracy and communism. It was assumed that communism represented an ideology of the collective while democracy represented an ideology of the individual. If we accept the transition to a complex organism, we may consider this conflict to be resolved, not in favor of one or the other, but rather in favor of a third category - an emergent collective formed out of diverse individuals. (822)

Bardoscia, Marco, et al. Statistical Mechanics of Complex Economies. Journal of Statistical Mechanics. Online April, 2017. Bardoscia, Bank of England, with Gaicomo Livan, University College London, and Matteo Marsili, Abdus Salam International Centre for Theoretical Physics, Trieste systems scientists trace a foundational basis for human commerce all the way to condensed matter physics. In our website context, in the latter 2010s, here is another case of a grand synthesis from human to universe as distinguished by the same universally active topologies and transitions. A further credit for Livan is the Systemic Risk Centre, London School of Economics and Political Sciences.

In the pursuit of ever increasing efficiency and growth, our economies have evolved to remarkable degrees of complexity, with nested production processes feeding each other in order to create products of greater sophistication from less sophisticated ones, down to raw materials. The engine of such an expansion have been competitive markets that, according to General Equilibrium Theory (GET), achieve efficient allocations under specific conditions. We study large random economies within the GET framework, as templates of complex economies, and we find that a non-trivial phase transition occurs: the economy freezes in a state where all production processes collapse when either the number of primary goods or the number of available technologies fall below a critical threshold. As in other examples of phase transitions in large random systems, this is an unintended consequence of the growth in complexity. Our findings suggest that the Industrial Revolution can be regarded as a sharp transition between different phases, but also imply that well developed economies can collapse if too many intermediate goods are introduced. (Abstract)

Bardoscia, Marco, et al. The Physics of Financial Networks. arXiv:2103.05623. Nine European systems scientists including Stefano Battiston, Giulio Cimini and Guido Caldarelli provide an integration of condensed matter physical principles with nonlinear complex network theories so to gain a quantified understandings from hyper-active money market economies. A prime intent is to better anticipate portfolio solvency, liquidity and contagions so as to mitigate.

The field of Financial Networks is a paramount example of the application of Statistical Physics now possible by way of the present data revolution. As the total value of the global financial market has outgrown the value of the real economy, financial institutions have created a web of interactions whose size and topology calls for a quantitative analysis by means of Complex Networks. In this review we present the state of the art in this field, from definitions of financial networks based on loans, assets, contracts to multiplex firms. We believe such complexity analysis about financial stability, along with climate dynamics, can aid movements towards a more sustainable world. (Abstract)

Barthelemy, Marc. The Statistical Physics of Cities. arXiv:1905.01953. A Centre d'Analyse et de Mathématique Sociale, Paris systems theorist continues his studies, notably akin to Michael Batty in London, to an extent that urban fractal self-organization dynamics can be traced to and viewed as condensed matter phenomena. Though not so put, our small and large concentrated human habitations appear to spontaneously emerge and exemplify a generative natural source and agency. A hundred plus reference list provides a broad two decade survey.

Challenges due to the rapid urbanization of the world -- especially in emerging countries -- range from an increasing dependence on energy, to air pollution, socio-spatial inequalities, environmental and sustainability issues. Modelling the structure and evolution of cities is critical because policy makers need robust theories and new paradigms for mitigating these problems. Statistical physics plays a major role in this effort by bringing tools and concepts able to bridge theory and empirical results. Here we focus on the distribution of the urban population; segregation phenomena and spin-like models; the polycentric transition of the activity organization; energy considerations about mobility and models inspired by gravity and radiation concepts and scaling that describes how socio-economical and infrastructures evolve when cities grow. (Abstract)

Barthelemy, Marc, et al. Velocity and Hierarchical Spread of Epidemic Outbreaks in Scale-Free Networks. Physical Review Letters. 92/178701, 2004. The spread of viral and infectious diseases based on a frequency of human contacts is found to take on a charateristic invariant topology. Learning this mathematical basis can then help inform containment strategies.

Batty, Michael. Cellular Automata and Urban Simulation. Environment and Planning B. 28/2, 2001. How this approach to complex systems can help model the development and viability of cities.

CA models of spatial complexity are used to advance understanding of general complex adaptive systems alongside similar models in the natural sciences. (164) Cities are fine examples of complex emergent systems. From local-scale interactions such as individual movement habits, the geomarketing strategies of retail establishments, social biases, and residential and lifestyle choices…aggregate patterns often emerge apparently independently of the dynamics driving the individual components of the system. Urban systems also display many traits common to complex systems in the biological, physical and chemical worlds. (165)

Batty, Michael. Building a Science of Cities. Cities. 29/Supp.1, 2012. The University College London systems geographer and leading theorist in this endeavor to quantify and show how human settlements of every size and place are iconic exemplars of the same nonlinear dynamic self-organization and fractal nestedness at work everywhere else from galaxies to genomes. Might one dub such studies, by way of their mathematical guidance, as urbanome or urbanomics, metrome and metromics?

Cities do not exist in benign environments and cannot be easily closed from the wider world, they do not automatically return to equilibrium for they are forever changing, indeed they are far-from-equilibrium. Nor are they centrally ordered but evolve mainly from the bottom up as the products of millions of individual and group decisions with only occasional top down centralised action. In short, cities are more like biological than mechanical systems and the rise of the sciences of complexity which has changed the direction of systems theory from top down to bottom up is one that treats such systems as open, based more on the product of evolutionary processes than one of grand design. (S9)

This idea of using morphology as a signature to detect the different underlying processes at work in cities relates very strongly to notions about how individual spatial decisions determine how cities grow from the bottom up and how patterns repeat themselves at different spatial scales. Urban development rarely fills the entire space which defines the wider hinterland of a settlement or city and in this sense, it is regarded as space-filling in the same way that fractal forms fill space between the Euclidian (integer) dimensions. The whole paraphernalia of fractal geometry can thus be brought to bear on urban patterns and processes. (S10-S11)

Batty, Michael. Cities and Complexity. Cambridge: MIT Press, 2005. Over a decade of analysis and simulation by the British urban planner of the growth and structure of human settlements via cellular automata, network science and nonlinear systems theory is here collected and summarized. As a result, cities are found to possess a mathematical basis as far-from-equilibrium, hierarchical, self-organized systems in a critical state between order and chaos. Of course we all pretty much know this. A large advance in understanding how such universal formative dynamics can apply from neighborhoods and congregations to a large urban metropolis such as London. See also a recent synopsis by the author in Science (319/769, 2008) on The Size, Scale, and Shape of Cities.

The fractal city is a recurrent theme throughout this book in that we argue….that the signature of urban dynamics is scaling – self-similarity and order on all scales, the hallmark of fractal geometry. (14)

Batty, Michael. Inventing Future Cities. Cambridge: MIT Press, 2018. The latest volume by the emeritus Professor of Planning at the University College London (search) who has been a leading urban complex systems theorist and real neighborhood to metropolis practical applier. I used his Fractal London image for a slide in 2005. Batty and colleagues draw upon mathematical methods of cellular automata, multiples network, dynamic self-organization and more in these studies.

Batty, Michael. The New Science of Cities. Cambridge: MIT Press, 2013. This consummate volume by the University College London geographer and urban planner well summarizes his pioneer studies upon the application of complexity theories, broadly conceived, to the spatial and temporal anatomy and physiology of urban settlements of every size. His corpus has set a standard for such widely used approaches as it draws on fractal self-similarity, cellular automata, self-organization, agent-based systems, space syntax, emergence, hierarchies, and especially dynamic networks. Search also Heppenstall and Biourbanism for examples of its adoption. A good review by Michael Szell in Science for February 28, 2014 (343/970) notes how this work quite implies “Universal principles that govern urban shapes and growth processes independently of particular history or geography.”

Complex systems that self-organize into clusters from the bottom up do show emergence, in that patterns established through rules at the lowest level repeat themselves at larger or higher scales. (27) The emergence of order on all scales is the hallmark of complex systems, and it is hardly surprising that with the growth of digital computation, it is now possible to simulate such evolutionary processes, there by suggesting how “good” designs might emerge among a universe of possible designs. (246)

Batty, Michael. The Size, Scale, and Shape of Cities. Science. 319/769, 2009. With his Centre for Advanced Spatial Analysis group and colleagues worldwide, the University College London systems geographer summarizes how the same generative geometries that imbue nature’s cellular forms everywhere are found to equally hold for and vitalize diverse urban settlements.

Despite a century of effort, our understanding of how cities evolve is still woefully inadequate. Recent research, however, suggests that cities are complex systems that mainly grow from the bottom up, their size and shape following well-defined scaling laws that result from intense competition for space. An integrated theory of how cities evolve, linking urban economics and transportation behavior to developments in network science, allometric growth, and fractal geometry, is being slowly developed. (769)

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